Modeling Of The Manufacturing Process Of Solid State Batteries H/F

Universities and Institutes of France
September 29, 2022
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Temporary
Working Time:Full time
Working type:N/A
Job Ref.:N/A
  • Organisation/Company: CNRS
  • Research Field: Chemistry › Computational chemistry Chemistry › Physical chemistry
  • Researcher Profile: First Stage Researcher (R1)
  • Application Deadline: 29/09/2022 23:59 - Europe/Brussels
  • Location: France › AMIENS
  • Type Of Contract: Temporary
  • Job Status: Full-time
  • Hours Per Week: 35
  • Offer Starting Date: 01/11/2022
  • Eu Research Framework Programme: H2020
  • Candidates should have a recent MSc. diploma or equivalent, with a solid background in computational techniques applied to materials, such as molecular dynamics or similar techniques. Candidates with some experience in machine learning will be also appreciated. Candidates having only experience in Density Functional Theory calculations or similar will be considered as having a background not suitable for the intended work in this PhD position.

    The chosen candidate will gain the opportunity to work in an international team with numerous opportunities of scientific networking.

    This is an opening PhD position in the group of Prof. Alejandro A. Franco, at the Laboratoire de Réactivité et Chimie des Solides, Mixed Research Unit at the Université de Picardie Jules Verne, in Amiens, France.

    The PhD postition is within the context of the European Project "PULSELION", recently granted, and is to start as soon as possible and not later than January 2023.

    The position is about the computational modeling of the manufacturing process of Solid State Battery cells, by using computational techniques such as Coarse Grained Molecular Dynamics and Discrete Element Method. For this purpose, the candidate will adapt several of the simulation tools previously developed in the ERC-funded ARTISTIC project https: // www. led by Prof. Alejandro A. Franco. The candidate will simulate the influence of manufacturing parameters on the electrode and cell microstructure and compare his/her results with experimental data obtained by the partners of the PULSELION project. The candidate will also have the chance to implement machine learning techniques to speed up the optimization of the manufacturing process.

    Web site for additional job details

    https: //

    Required Research Experiences
  • Chemistry › Physical chemistry

  • None

  • Chemistry › Computational chemistry

  • None

    Offer Requirements
  • Chemistry: Master Degree or equivalent

  • FRENCH: Basic

    Contact Information
  • Organisation/Company: CNRS
  • Department: Laboratoire de réactivité et chimie des solides
  • Organisation Type: Public Research Institution
  • Website: https:// www.
  • Country: France
  • City: AMIENS
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